Level and Duration of the Program: Master, 4 Semesters.
Data Science Engineering Master's Program Mission
The objective of the Data Science Engineering Master's Program is to impart to students the fundamental principles, techniques, and applications of data science, with the ultimate goal of fostering analytical thinking and engineering proficiency. Furthermore, the program strives to offer students hands-on experience in the creation of data science projects that align with current industry requirements, while simultaneously cultivating their research capabilities and urging them to devise sustainable solutions.
Data Science Engineering Master's Program Vision
The Data Science Engineering Master's Program seeks to equip students with the competencies necessary to lead in the data-driven future and to propose innovative solutions to the industry. The program intends to provide students with extensive analytical capabilities, strong engineering proficiencies, and a multidisciplinary outlook, enabling them to stay current with the latest advancements in the field of data science. Additionally, the program emphasizes the importance of ethical considerations and social impact, helping students to develop sustainable solutions.
Program Purpose: The objective of the Data Science Engineering Master's Program is to impart education to students with an emphasis on the following priority areas:
1. Basic Data Science Knowledge and Skills: To offer students a comprehensive understanding of crucial data science concepts, including data mining, statistics, machine learning, and big data technologies.
2. Development of Engineering Capabilities: To afford students the chance to hone their engineering proficiencies in areas such as data infrastructure, databases, parallel computing, and data security.
3. Applications and Project Development: To offer students practical experience in working on actual projects and to enable them to create data science applications that meet industry standards.
4. Analytical and Critical Thinking Skills: To improve students' ability to analyze, analyze and interpret data sets.
5. Communication and Collaboration Skills: To impart the skills necessary for presenting data science projects in an effective manner, as well as fostering teamwork and communication with relevant stakeholders.
6. Research and Innovation Capabilities: To equip students with the capability to carry out research in the realm of data science and to motivate them to devise novel solutions.
Program Outcomes: The achievements of the Data Science Engineering Master's Program are as follows:
1. Data Science Fundamentals: In-depth knowledge of basic data science topics.
2. Engineering Capabilities: Development of engineering skills such as data engineering, big data processing, and database management.
3. Practical Applications: Ability to develop industry-standard data science applications by working on real-world projects.
4. Analytical and Critical Thinking: Developing the ability to critically analyze and evaluate data sets is a valuable skill to acquire.
5. Communication and Collaboration Skills: Enhancing proficiency in presenting data science initiatives, collaborating with colleagues, and engaging with stakeholders in a productive manner.
6. Research and Innovation: The ability to produce innovative solutions by providing research skills in the field of data science.
7. Ethics and Social Responsibility: Ability to understand ethical responsibilities related to data use and to assess societal impacts.
Program Employment Areas: Graduates of the Data Science Engineering Master's Program have a broad range of employment opportunities across multiple sectors. The following are some of the possible employment areas:
1. Technology Companies: Data science engineer positions in big tech firms.
2. Finance Sector: Professionals skilled in data science, particularly in the realms of risk assessment and customer segmentation, are employed by financial institutions like banks and insurance companies.
3. Health Sector: Expertise in patient data analysis, disease prediction and treatment planning in healthcare organizations.
4. Retail and E-Commerce: Professionals skilled in data science, particularly in the fields of demand forecasting and customer behavior analysis, are prevalent in the retail industry.
5. Energy and Natural Resources: Opportunities to work in the areas of operational efficiency, energy forecasting, and resource management in energyorganizations.
6. Telecommunication: Experts in data science with a focus on network optimization and customer satisfaction analysis are commonly found in telecommunication companies.
7. Corporate Services: Opportunities available to work on data science and analytics projects within government agencies, city governments, and public services.
Courses Process: The Data Science Engineering Master's Program employs an internet-based Learning Management System (LMS) as its mode of instruction. Through this platform, students are able to attend classes remotely and complete the program.
Bölüm Müfredati / Department Curriculum